# This is an example extension for custom training. It is great for experimenting with new ideas. from toolkit.extension import Extension # This is for generic training (LoRA, Dreambooth, FineTuning) class AdvancedReferenceGeneratorExtension(Extension): # uid must be unique, it is how the extension is identified uid = "reference_generator" # name is the name of the extension for printing name = "Reference Generator" # This is where your process class is loaded # keep your imports in here so they don't slow down the rest of the program @classmethod def get_process(cls): # import your process class here so it is only loaded when needed and return it from .ReferenceGenerator import ReferenceGenerator return ReferenceGenerator # This is for generic training (LoRA, Dreambooth, FineTuning) class PureLoraGenerator(Extension): # uid must be unique, it is how the extension is identified uid = "pure_lora_generator" # name is the name of the extension for printing name = "Pure LoRA Generator" # This is where your process class is loaded # keep your imports in here so they don't slow down the rest of the program @classmethod def get_process(cls): # import your process class here so it is only loaded when needed and return it from .PureLoraGenerator import PureLoraGenerator return PureLoraGenerator # This is for generic training (LoRA, Dreambooth, FineTuning) class Img2ImgGeneratorExtension(Extension): # uid must be unique, it is how the extension is identified uid = "batch_img2img" # name is the name of the extension for printing name = "Img2ImgGeneratorExtension" # This is where your process class is loaded # keep your imports in here so they don't slow down the rest of the program @classmethod def get_process(cls): # import your process class here so it is only loaded when needed and return it from .Img2ImgGenerator import Img2ImgGenerator return Img2ImgGenerator AI_TOOLKIT_EXTENSIONS = [ # you can put a list of extensions here AdvancedReferenceGeneratorExtension, PureLoraGenerator, Img2ImgGeneratorExtension ]